Why AI fluency is now Canada's most urgent HR imperative

Artificial intelligence (AI) is no longer a future consideration for Canada's human resources (HR) leaders – it’s a present-day operational reality. But as adoption accelerates across the employee lifecycle, a widening divide is emerging between organizations that are transforming with real AI fluency and those scrambling to keep pace. With Ontario's AI disclosure rules now in force and federal legislation on the horizon, the pressure on HR executives in 2026 is increasing, but genuinely applicable governance is lagging behind the technology, according to Joanna Kmiec, Chief People Officer at Loopio in Toronto. 

"There's a lot of everything on the fly and learning right now – we’re all leading without the time to create the perfect plan," says Kmiec. "Things don't change every few years or even every few months anymore. It's almost daily." 

What Kmiec says she’s seeing across the industry reflects a profession at vastly different stages of readiness. Some organizations are distributing AI tools with no broader strategy – using them to draft job descriptions or internal communications and little beyond that. Others have swung in the opposite direction, becoming so focused on governance frameworks that forward movement has stalled entirely. At Loopio, Kmiec is pursuing a third path: full, structured transformation. "You can't be holding back because it’s moving with or without you," she says. 

Measured transformation versus piecemeal adoption 

That transformation is built across three tiers, according to Kmiec: a company-wide overhaul of systems and technology, team-specific AI adoption mapped to each function's distinct needs, and individual fluency programs blending self-directed learning with structured enablement. 

Bruce Weippert, President and Senior Strategist at TAP Strategy & HR Consulting in Toronto, has observed the same divide from the consulting side. Larger organizations with the infrastructure, expertise, and funding are considerably further ahead, while smaller businesses and not-for-profits, by contrast, are frequently improvising – uploading resumes into a chatbot and calling that their AI strategy. "You don't know what you don't know," says Weippert. "What you want to do is move individuals to conscious incompetence at minimum, so that they now know what they don't know and they want to start looking into it and fixing it." 

The risks of leaving adoption to individual initiative are real, he says. "Leaving it to the masses to make their own decisions to hire, purchase, or adopt piecemeal solutions is going to create havoc within the organization." 

Appetite for AI, willingness to learn 

One of the most concrete ways AI is changing HR is in how organizations are hiring for it. According to ADP Canada's workplace trends for 2026 report, 75 per cent of large organizations view AI as essential – yet only 13 per cent prioritize hiring for AI skills. 

Part of this hiring disconnect could be from leaders from older generations who don’t see the full value of AI skills and the rapid pace of technology, says Weippert. 

“In our work, we find that there's a definite appetite for AI and for automated processes, but we see a definite difference between those in younger generations and those in older generations,” he says. “Organizations can lack the foresight because they're comfortable with the way things have always been done, and AI can be scary.” 

At Loopio, Kmiec has built a structured AI fluency framework into hiring, mapping candidates against levels from beginner to expert. She says the goal isn’t technical proficiency, but rather mindset. "It's not always about how much you've done, it's more about the openness to try and learn,” she says. “It's that curiosity, that hunger to learn, and to learn different ways of doing things, that we're really intentionally looking for, because if you've got that, then whichever tools get put in front of you, you’ll find a way to make them work." 

Determining where people are still essential 

Where AI is having the most immediate impact in HR functions is in talent acquisition and onboarding. Screening, interview note summarization, and workflow automation have reduced manual workloads considerably, but the boundaries of automation must be deliberate, says Kmiec. 

"The key here is to automate the work that can be automated so that a number of workflows are happening without the human needing to be a part of every step," she says. "That being said, you do need to evaluate the entire employee journey to see where automation makes sense and make very intentional decisions of where a human needs to remain in the loop." 

Performance reviews are one area Kmiec believes people need to remain a part of. Summaries can serve as useful preparation, but the conversation itself must stay human. "You should be giving that feedback live – there are levels of context that AI doesn’t always get right," she says. "You don't want to outsource everything to AI because, at the end of the day, employees still want that sense of belonging and that sense of connection." 

Weippert sees the longer-term risk in fragmentation. "Without having a seamless integrated HR model that uses AI effectively with a human touch, you’ll create barriers and erode trust in an organization, which could ultimately affect the organization’s culture if it's not done well." 

Governance caught between two speeds 

Ontario's Working for Workers Four Act, 2024, which came into force in January 2026, now requires employers with 25 or more employees to disclose the use of AI in screening, assessing, or selecting candidates in publicly advertised job postings. Bill C-36, the proposed Protecting Privacy and Consumer Data Act (PPCDA), tabled by the federal government in June, signals that a national AI accountability framework is coming. Both developments are reshaping how Canadian organizations approach employment law compliance and HR governance obligations involving AI. 

For Kmiec, the regulatory picture reflects a structural lag. "I don't think real applicable governance is moving as quickly as the technology," she says. "We see a lot where an AI tool in an organization has something happens, you see where it went wrong, and then the legislation is coming to protect after the fact – one law that gets created today will likely need to be amended very, very soon after it's created." 

She also points out how some organizations go too far in the other direction, where an organization’s governance is too specific and rigid, which can hinder the development of efficient and productive AI use. "HR needs to be a part of the conversation so that when you’re creating governance for your organization, you’re looking at it from all lenses, not just the IT and the legal lens, also from the people lens," says Kmiec. 

Kmiec believes that when HR, legal, and technology leads work together, organizations are far better positioned to progress without stifling productivity or growth. 

The opportunity for those willing to lead by example remains significant. Kmiec's vision for where AI should ultimately take HR is away from the administrative treadmill and toward the strategic role the function has long sought, freeing up time to transform the entire organization strategically. "The biggest opportunity is going to be for those HR teams that aren’t afraid of this, that are willing to lean into this wave and to truly transform work," she says. "It will free them up to be the strategic function that it needs to be, and it's always been held back by being too busy putting out fires." 

This article is part of our Monthly Spotlight series, which in August focuses on AI in HR. Full coverage can be found here.